Skill UI

Access the ClinicalTrials.gov API v2 to search trials by condition, drug, location, sponsor or status, fetch details via NCT ID, and export JSON/CSV data for research analysis, patient matching, and trial monitoring.

Query and download the NCI Imaging Data Commons public cancer imaging datasets via idc-index, filter by metadata, fetch DICOM files, visualize series, and respect licensing details for AI training or research.

Query the NIH Metabolomics Workbench via REST API to fetch metabolites, RefMet nomenclature, mass-spec searches, and detailed study datasets for biomarker discovery and metabolomics research.

QuTiP is a Python toolbox for simulating open and closed quantum systems, offering solvers for master equations, trajectory methods, visualization, and analysis tailored to quantum research, education, and exploratory physics studies.

Conversational research ideation assistant that helps scientists generate novel hypotheses, explore interdisciplinary analogies, challenge assumptions, and outline experiment pathways during early-stage planning.

Literature Review Tool helps researchers gather and synthesize key insights from scholarly texts, highlighting patterns and critical arguments to accelerate literature surveying workflows even when structured content is initially unavailable.

A comprehensive tool designed to search, download, and summarize academic papers from the arXiv repository. Users can search by topic or specific ID, manage result limits, and save PDFs locally. The system extracts detailed metadata, provides abstract summaries, and identifies key research contributions.

This skill systematically verifies the novelty of a proposed research method or idea against vast global literature. It identifies core technical claims, performs multi-source searches across arXiv, Google Scholar, and major conferences (ICLR, NeurIPS, ICML), and utilizes advanced LLMs for cross-model verification. The output is a structured report, providing a novelty score, identifying the closest prior work, and offering a strategic recommendation to guide the research direction.

Utilize this skill to simulate an intensive, multi-round expert peer review process (NeurIPS/ICML level) for academic research, paper drafts, or project ideas. It conducts a deep critical analysis, helping users identify logical gaps, missing experiments, narrative weaknesses, and refining the core contribution claims through iterative, highly structured dialogue.

This gate systematically evaluates experimental outcomes against intended research claims. It collects metrics from various sources (W&B, logs, etc.) and uses an objective judgment model to determine if the data supports, partially supports, or fails to support the hypothesis. It provides specific evidence gaps and suggests concrete next steps, guiding the research workflow before writing papers or finalizing designs.

A powerful tool for searching published, peer-reviewed academic literature from major venues like IEEE, ACM, and Springer. Unlike preprint archives (like ArXiv), this skill provides robust metadata, including citation counts, official publication venue details, and TLDR summaries. Use it when you need verified, finalized research papers and advanced filtering capabilities.

This tool functions as a persistent, structured knowledge base for the entire research lifecycle. It accumulates and maps all core research entities—including published papers, generated ideas, experiments, and testable claims—along with their complex relationships (e.g., contradiction, support, inspiration). Inspired by LLM Wiki patterns, it ensures that knowledge is compounded and perpetually queryable, moving beyond single-use literature reviews.